Should Developers Be Excited Or Worried About GPT-4?

How worried should you be? (if at all)

It’s likely you’ve heard a significant amount of buzz about GPT-4 recently. And depending on your stance on game-changing technology (and believe us, this is potentially game-changing), you’re likely either welcoming it with arms wide open or cursing its very existence.

The truth is, of course, that AI language tools such as ChatGPT and its rival Google Bard will impact — and in many cases, are already impacting — almost all industries in some shape or form. For better or worse, software development is certainly one area that will be shaped by artificial intelligence over the coming years, with many developers surely wondering how the technology will affect their roles and their livelihoods.

So, is GPT-4 a good or a bad thing for developers? Should its increasing influence cause excitement or apprehension among the developer community? Let’s explore how GPT is likely to impact developers.

So, what _is_GPT-4?

GPT-4 (or Generative Pre-trained Transformer 4, to give it its full name) is the latest version of OpenAI’s large language model, which utilizes a machine learning technique called “Transformer” that allows it to generate coherent and contextually-relevant sentences (when provided with a prompt) by predicting subsequent words within a given piece of text.

Prior to the release of GPT-4, the previous iteration (GPT-3.5) formed the foundation of advanced chatbots such as ChatGPT, while this most recent version has many more progressive features, such as the ability to accept multimodal inputs — meaning it can accept and produce text and images. GPT-4 is also more accurate than its predecessor (which was more prone to “hallucinations”), principally because it’s trained on a much larger data set.

And while chatbots — which use a similar type of natural language processing (NLP) technology — have been around for a while (take Drift, for example, or Crisp, a popular Drift alternative), AI language models such as ChatGPT are far more sophisticated than these more primitive forerunners, which typically use pre-programmed rules to simulate interactions and provide appropriate responses based on specific triggers.

Unlike rule-based or simple machine learning chatbots, however — which depend on pre-set responses or limited learning from labeled datasets — GPT-4 leverages unsupervised learning from a vast corpus of internet text, enabling it to handle complex and nuanced conversations and construct dynamic responses to questions and prompts — from generating content, to assisting with research, to writing and debugging code.

Should developers be worried about GPT-4?

Sure, GPT-4 is capable of writing code. In fact, it’s pretty good at it. It can also debug and refactor code, generate code snippets, and explain advanced coding techniques and concepts. But does this mean that all developers should start rethinking their career options? Is the technology going to wipe out developer jobs over the next few years?

It’s inevitable that many developers have considered these worst-case scenarios in recent months, such is the potential impact of ChatGPT and copycat tools such as Bard, Microsoft’s Bing Chat, and ChatSonic. It can’t be denied that GPT-based technology will have significant repercussions across many industries — and development is no exception — but there are reasons to be hopeful.

The reality is, while ChatGPT has little trouble completing fairly routine coding tasks, complex software development requires the kind of critical thinking, creativity, and advanced problem-solving capabilities that only an experienced, human developer is currently able to achieve — it’s unlikely that developers will be rendered obsolete by GPT-4 (or any of its subsequent iterations) anytime soon.

In fact, the increasing adoption of AI and automation is more likely to lead to shift in job responsibilities — even enabling developers to concentrate on more high-level tasks by automating the most manual and time-consuming parts of their roles — rather than industry-wide job losses, while a demand for new skills will inevitably emerge, potentially creating new opportunities and development pathways.

The developer community should also remember that GPT-4, while considerably more advanced than its preceding iterations, is still far _from perfect. OpenAI says GPT-4 is 40% more likely to provide “factual responses”, but it’s still guilty of inaccuracies (and in some cases, outright fabrication). It’s also true that in many cases, the tool’s output is only _really effective if you provide it with a very clear and descriptive prompt in the first place — and those prompts, of course, must be inputted by a human.

Reasons that GPT-4 could be a good thing for developers

While many developers will surely remain wary of this increasingly ubiquitous technology, the outlook isn’t necessarily all doom and gloom. Let’s focus on the positives for a moment, and consider the reasons that developers might actually welcome the advent of GPT-4 and all the capabilities it offers.

  • It can save developers time. GPT-4 can speed up software development by generating code snippets based on given prompts, reducing the time spent writing code from scratch. It can also be trained to generate documentation — a vital but time-consuming task for developers — which not only saves time, but also helps maintain consistency in the way documentation is written across a codebase.
  • It can automate the ‘boring’ stuff. From writing routine emails to creating standard code structures, developers often find themselves performing repetitive tasks. GPT-4, being a sophisticated language model, can learn the patterns associated with these tasks and automate them, freeing up developers to focus on more complex and engaging tasks.
  • It can improve code quality. By learning from a large corpus of programming examples, GPT-4 can generate code snippets, identify potential bugs, and suggest possible optimizations. This can be particularly useful for ensuring accurate and high-quality code when a developer is learning a new programming language or working with unfamiliar libraries.
  • It can provide suggestions and recommendations. GPT-4 can provide context-aware suggestions and recommendations based on code you’ve already written. By training the tool on previous datasets, it could potentially highlight inefficient sections of code, spot bugs and errors, and recommend more economical ways to structure the code.
  • It can help developers learn. Yes, GPT-4 can be used as a learning tool for developers. By generating explanations and examples, it can help developers to understand new programming languages or complex coding concepts, which can significantly shorten the learning curve and provide a more interactive learning experience.
  • It can help create testing scenarios. Robust software testing often requires the generation of diverse and complex test scenarios. With its ability to generate varied and contextually-relevant text, GPT-4 can be used to create these scenarios, ensuring that software is tested against a wide range of situations. This can help developers catch and fix bugs early, improving the overall reliability of software.

So, should developers be excited or worried about GPT-4? It remains to be seen how the technology will develop in the coming years (and the impact this will have), but there’s nothing to suggest human developers will be left out in the cold just yet. And as we’ve discovered, there are ample reasons why tools such as ChatGPT can actually be highly useful for developers if used effectively.

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